code: def testPNA():
      import dgl
      from deepchem.models.torch_models.pna_gnn import PNA
  
      data, _ = get_regression_dataset()
      features = dgl.batch(
          [conformer.to_dgl_graph() for conformer in data.X]
      )
      target_dim = 1
      model = PNA(hidden_dim=16, target_dim=target_dim)
      output = model(features)
      assert output.shape[1] == target_dim
  
file_path: deepchem/deepchem/models/tests/test_pna.py
imports: import os
  import numpy
  import deepchem
  import pytest
label_desc: Use image node_id 6 for calling a global function with example usage: testPNA() without return types